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## gist:a64010915eccda2ccaa527199bcfd323
# Workflow Orchestration

## 1. Plan Mode Default

- Enter plan mode for ANY non-trivial task (3+ steps or architectural decisions)
- If something goes sideways, STOP and re-plan immediately — don't keep pushing
- Use plan mode for verification steps, not just building
- Write detailed specs upfront to reduce ambiguity

## 2. Subagent Strategy

## mlil_slice.py
from binaryninja import HighlightStandardColor, PluginCommand


def do_backward_slice(instruction, function):
    # switch to SSA form (this does nothing if it's already SSA).
    instruction_queue = set([instruction.ssa_form.instr_index])
    visited_instructions = set()

    variables = set()

## README.md

      
              1 file
            
          
              23 forks
            
          
                12 comments
              
            
              41 stars
            
          
                cweilouis
                / README.md
            
            
              Created
              April 17, 2025 01:45
            
              
                Free Activation Code for JetBrains Products
              
          
    My greetings, for everyone.

How to activate any JetBrains products with 3.jetbra.in?

First we need to visit this website


https://3.jetbra.in

Click the first link with Online status, by default is ipfs.io


## 001_NEW27_task_overview.txt
# Owning binary : TextComposerRuntime
# Status        : NEW in iOS 27 (not in 26.5.1)
# Source        : embedded __cstring in dyld_shared_cache_arm64e (24A5355q)
======================================================================

    # Task Overview:
    You are a composition agent that helps users create personalized written content (emails, messages, documents, posts, stories, etc.)

    As an Assistant, you must:
    1. Analyze the request to determine if you have sufficient information

## prompt.md

      
              1 file
            
          
              139 forks
            
          
                77 comments
              
            
              337 stars
            
          
                Pythonation
                / prompt.md
            
            
              Last active
              June 11, 2026 08:30
            
              
                3 PROMPTS OF CODING AGENTS
              
          
    1. برومبت التخطيط المطوّر (The Planning Protocol)


[الدور والمسؤولية]
أنت الآن تعمل بصفة Staff Software Engineer ومدير تقني Tech Lead. مهمتك التخطيط المعماري الصارم للمشروع التالي:
[أدخل وصف المشروع هنا]
[قواعد ما قبل التتخطيط]
قبل البدء بالبروتوكولات، يجب أن تطبق مبدأ "Think Before Coding":


## AGENT.md

      
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              1 star
            
          
                c1982
                / AGENT.md
            
            
              Created
              June 8, 2026 21:16
            
              
                My excample AGENT.md for llm-wiki
              
          
    NovaWiki — LLM Wiki Schema (Example)


Example file for articles and onboarding.

Pattern inspired by Andrej Karpathy's LLM Wiki.

Replace placeholders (Nova Arena, domain names, paths) with your product.

This file is the schema layer: it tells the agent how to maintain the wiki.

Humans rarely edit wiki pages by hand — the agent writes and updates them.


## prompt.md

      
              1 file
            
          
              1 fork
            
          
                5 comments
              
            
              13 stars
            
          
                cnemri
                / prompt.md
            
            
              Created
              June 10, 2026 10:57
            
              
                Claude Fable 5: Sidi Bousaid 3D prompt
              
          
    Write a complete, production-ready, single-file HTML/JavaScript application that renders a highly detailed, photo-realistic, navigable 3D scene of the iconic cliffside village of Sidi Bou Said, Tunisia using Three.js.
CRITICAL INSTRUCTIONS — NO LAZY CODE


Do NOT use any external asset URLs (no external .gltf, .obj, .jpg, or .png files) as they can break or fail CORS. All textures, heights, and models must be generated dynamically and procedurally within the script (e.g., using HTML Canvas to draw textures, procedural noise algorithms for plaster and stone, or mathematical structures for 3D meshes).
Do NOT write placeholder comments, truncated code blocks, "// TODO" markers, or "left as an exercise" shorthand. Every single function, shader, loop, and variable must be written out in its entirety.
The output must be a single, copy-pasteable HTML file that runs perfectly immediately when opened in a browser.

TECHNICAL REQUIREMENTS & FEATURES


Libraries: Load Three.js and OrbitControls vi


## llm-wiki.md

      
              1 file
            
          
              7724 forks
            
          
                887 comments
              
            
              36638 stars
            
          
                karpathy
                / llm-wiki.md
            
            
              Created
              April 4, 2026 16:25
            
              
                llm-wiki
              
          
    LLM Wiki

A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

  
## microgpt.py
"""
The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
This file is the complete algorithm.
Everything else is just efficiency.

@karpathy
"""

import os       # os.path.exists
import math     # math.log, math.exp
	# Workflow Orchestration

	## 1. Plan Mode Default

	- Enter plan mode for ANY non-trivial task (3+ steps or architectural decisions)
	- If something goes sideways, STOP and re-plan immediately — don't keep pushing
	- Use plan mode for verification steps, not just building
	- Write detailed specs upfront to reduce ambiguity

	## 2. Subagent Strategy
	from binaryninja import HighlightStandardColor, PluginCommand


	def do_backward_slice(instruction, function):
	# switch to SSA form (this does nothing if it's already SSA).
	instruction_queue = set([instruction.ssa_form.instr_index])
	visited_instructions = set()

	variables = set()
	# Owning binary : TextComposerRuntime
	# Status : NEW in iOS 27 (not in 26.5.1)
	# Source : embedded __cstring in dyld_shared_cache_arm64e (24A5355q)
	======================================================================

	# Task Overview:
	You are a composition agent that helps users create personalized written content (emails, messages, documents, posts, stories, etc.)

	As an Assistant, you must:
	1. Analyze the request to determine if you have sufficient information
	"""
	The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
	This file is the complete algorithm.
	Everything else is just efficiency.

	@karpathy
	"""

	import os # os.path.exists
	import math # math.log, math.exp